Labor market performance gaps and the role of secondary vocational education at meister high school in Korea

Abstract

This study explored the mechanism of labor market performance by confirming the role of secondary vocational education for young Korean employees of high school graduates. To this end, we focused on the Meister High School (MHS) policy for fostering the lead in secondary vocational education in Korea. In comparative perspective, data from 2,344 Korean employees who graduated from MHS or Specialized Vocational High School (SVHS) were analyzed. Firstly, it was found that MHS graduates obtained better objective performance conditions even if the crucial reginal and parental effects are controlled. Next, MHS graduates maintained higher job satisfaction focusing on their horizontal mismatch level. Moreover, MHS graduates with higher achievement in vocational courses were satisfied with their school life. Our findings found the significant roles of the Korean secondary vocational education policy by applying assumptions of the status acquisition model.

Keywords:

• labor market performance
• young Korean employees
• secondary vocational education
• meister high school
• status acquisition model

1. Introduction

Among Asian countries, the preference on the college entrance has led to a craze for entering academic high school. In South Korea, there was a huge fever for going to high school, and in the end, the rate of going to school reached 71.5% in 2007, which exceeded the employment rate (S. N. Kim et al., 2019). Due to this phenomenon, there was an imbalance in the supply and demand of industry personnel, weakening national competitiveness. In addition, high additional costs for re-education were consumed in the industry due to the skill mismatch problem of high school-level vocational education institutions (Ministry of Education, Science and Technology, 2008). The match between majors and occupations of vocational high school graduates was also very low. In 2008, students could not make a career decision due to low treatment (remuneration, working conditions; S. N. Kim et al., 2019). It was necessary to solve the problem caused by the identity crisis of the specialized vocational high school due to such formal industry-university connection and job evasion (S. N. Kim et al., 2019).

Accordingly, the Korean government has found a solution of skill mismatch in human resources training at the vocational high schools and educational institutions. It presented in the <High School Diversification 300 Project> and proposed a “Plan to Develop Korean-Style Meister High School (MHS)” as a new role model for vocational high schools. The purpose of the project is to promote the diversification, specialization, and autonomy of secondary education to supplement uniformity while maintaining the basic framework of the current high school equalization system. Therefore, the Korean-style Meister High School Basic Plan was announced to foster leading and excellent vocational high schools (Park et al., 2020).

The background of MHS policy started from criticism of vocational high schools in the late 2000s. Korea’s vocational education policy in the 1970s and 1980s has greatly contributed to nurturing the human resources necessary for economic and industrial development in the high school stage. However, there have been continuous criticisms of vocational education for failing to nurture human resources suitable for accelerating knowledge and technology development according to economic environment changes (Na et al., 2007).

The core purpose of introducing MHS was to foster Korea’s root industry and maintain the continuity of the technological generation by providing vision and hope so that students can grow into experts in the desired industry according to their aptitudes and talents. This project aimed to nurture professional workforce that could be put into the field immediately after graduation by operating a curriculum tailored to industrial needs for three years in high school. With this aim, it established MHS as an excellent education model by enabling career development and “Employment first, College later” through stable employment. However, in South Korea, where education policies change rapidly whenever the government changes, the introduction of a new policy called Meister High School has raised concerns in the field of education. Despite these concerns, the school opened in 2010. Until 2022, the government has changed four times and is the only one that continues to receive support from the government (Yu et al., 2020; Yu & Lee, 2020).

MHS’s outcome has recorded an employment rate of more than 90% over the past five years since the first graduate. Since then, the performances of MHS graduates on the employment rate and job security indicators have been more positive than that of the general vocational high schools.

Nevertheless, it is pointed out that MHS students with a high-level family backgrounds, such as parental education, have a difference in labor market performance from other vocational high school graduates. Yang and Kim (2014) attempted to analyze whether MHS’s outcome was a pure school effect as an educational policy. Furthermore, the personal tendencies of MHS students were confirmed that their parents’ educational status increased. N. Kim (2019) pointed out that the employment rate in 2013, when MHS students first graduated, may have been temporarily overestimated compared to other high schools. These studies meant that the MHS policy effects in charge of secondary vocational education were related to various factors as a major influence on student’s achievement even if the policy effects were revealed.

However, we need to note that schooling is a key device supporting the industrial society and has developed in response to social changes while maintaining a close relationship with the labor market. This study intends to examine whether there is a difference in the labor performance of high school graduates according to their parents’ socioeconomic status and whether there is a different school effect of between MHS graduates and regular vocational high school graduates.

2. The historical and theoretical background

Along with this establishment background, it is necessary to consider the historical and theoretical background related to the establishment of MHS. First of all, in the background of the school establishment, it is also closely related to the fact that the government has led the nurturing of skilled workers in the process of industrial development in Korea, which has formed the skilled generation.

Since the 1970s, when Korea began to industrialize in earnest, information technology has been widely applied to industries. In the case of Korea, a latecomer, informatization society through computers proceeded simultaneously the following mechanization. Therefore, in terms of skill, it can be seen that the traditional skill and the new skill developed simultaneously with some time lag. However, traditional skills appeared first, which were also handed down from older generations. Also, in the case of excellent artisans represented by masters, right after learning traditional skills, they acquire new skills again, go to a new stage, and rather lead the automation and information process so that they can easily acquire and embody new skills. In the period when the skilled generation was being formed, in Korea, in the process of economic development led by the state, the state directly led the establishment of technical high schools, reorganizing the vocational education and training system, and supplying and retaining technical talents through special military force. As a result, policies poured out (Cho et al., 2013).

Second, it is necessary to consider that establishing vocational high schools as a state-led elite education is also related to neoliberal education policies and neoconservative policies. Around the 1990s, neoliberal education emerged rapidly. The direction of neoliberalism was macroscopically entered into a system of free competition between countries. At a small level, individual freedom was maximized, and the principle of free competition in the market was taken as an ideological standard (Kang, (2011).

In this regard, the neoliberal education center emphasized the marketization and commercialization of education and demanded that education be improved by introducing the principle of free competition in the market. Furthermore, the neoliberal education center gave education consumers the right to choose a school and education providers the right to self-manage, providing an ideological basis for closing schools with poor-quality education products according to the principle of market competition.

The Korean government has explicitly emphasized the entrepreneurial mindset of education from elementary and secondary education to higher education. Since then, market-friendly terms such as autonomy, competition, consumer centricity, and service have been used. In addition, course, school evaluation system were proposed (Kang, 2014, Kim, 2014).

After that, the Lee Myung-bak administration inherited and expanded the previous administration policies in terms of education policy. The reason was to create a competitive structure for entrance exams favorable to neoliberal political forces. Specifically, the number of autonomous private high schools was expanded from the previous government’s pilot program to 100, and as an extension of this, the <high school diversification 300 project> was implemented. In particular, the project aimed to establish 100 autonomous private high schools, 150 boarding-type public high schools, and 50 MHSs to secure diversity in high school education (B. J. Kim, 2014). MHS was defined as a high school tailored to industrial needs in Article 90 of the Enforcement Decree of the Elementary and Secondary Education Act, Paragraph 1, No. 10, and was established as a special purpose high school. Although it is a special purpose high school, it was started in 2010 for elite education within the top 10% of middle school grades at the time of its opening. Among the policies that MHS is taking, the open nature of the high school principal also carries the character of superiority in that a high school principal can become a principal with fair opportunities and excellent abilities depending on the market.

This neoliberal policy is also related to the neoconservative education policy. Since the 1980s, it has been common to define the character of education reform in the UK and the US as “neoliberal” (Apple, 2006). First, “small government-oriented” measures were taken, such as reducing government spending on public education and involving private management in school operations. The implementers of this policy are saying that they will improve the quality of education through competition on the supplier side.

However, the changes brought about by these neoliberal educational reforms within the educational world, especially at the curriculum and class level, emphasize the strengthening of the central government’s role in determining educational content, traditional subjects and discipline, and emphasis on intellectualism. Therefore, it tends to be far from the neoliberal philosophy of autonomy and competition. (Apple, 2006; Young & Levin, 1999).

Neoliberalism and neo-conservatism are like two sides of the same coin: autonomy and competition among suppliers is possible through standardization of educational contents and standardized tests, and standard curriculum and tests have resulted in the intellectualism of educational methods (Y. S. Kim, 2009). As a special purpose high school, Meister High follows the principle of a free and competitive market to meet industrial demand. However, the role of the central government, the Ministry of Education, has been strengthened in educational management. In the educational method, discipline between teachers and students and intellectualism are emphasized, so it can be said that it is far from complete autonomy in educational operation (Cho et al., 2013; B. H. Lee, 2002).

Third, it can be said that the historical relationship between Korea and Germany also affects the birth of MHS. Why was the German-style name of Meister given to the secondary vocational education system? During the Park Chung-hee administration in the 1960s and 1970s, when Korea’s economy and industry were developing, Korea faced a shortage of domestic capital when he came to power, but relations with the United States were not smooth. For this reason, as he opened his hand to West Germany for the purpose of introducing a loan, he became closer to Germany and visited West Germany (December 1964), which became an opportunity. Looking at Germany’s so-called “Miracle on the Rhine”, Park Chung-hee found the driving force behind the miracle of the Rhine River in post-war Germany to be the character of the Germanic people, namely, he found it in the role of “good leader” (B. C. Lee, 2015). Johnson (1995) identified Germany, Japan, and Korea as belonging to a common development line as a successful late-growth system based on vertical public-private cooperation, that is, a “capitalist developing country” model. He viewed the capitalist developed state of the Bismarck-Meiji-Park Chung-hee lineage based on the synergy between market and planning as a “planned rational” state. (B. C. Lee, 2015; Johnson, 1995)

3. Theoretical framework—status acquisition model

This study designed a mechanism of the labor market performance for young Korean employees of high school graduates by synthesizing the following discussion changes about secondary education experiences and social status.

In this regard, Blau and Duncan (1967) examined the relationship between the educational system and experiences in the professional world through the Status Acquisition Model (SAM). In other words, the educational experiences were considered to mediate between the social background that determines an individual job status and the social status to be achieved since then. Moreover, there are four significant factors influencing the acquisition of job status: father’s education, father’s job, student’s education experience, and student’s first job. As a result of tracking the prediction factors on job status acquisition, it was concluded that personal education experience and initial job experience greatly influenced job success, and these influences were stronger than social status. This model, which emphasizes the influence of educational experience, is projected Korea’s MHS policy that aims to grow students into a professional workforce by acquiring practical knowledge tailored to industrial needs during the three years of high school.

Here, as a complementary model, a more sophisticated model by adding social and psychological characteristics through students’ educational activities was highlighted by Sewell et al. (1969). The design variables of the Wisconsin model emphasized the importance of ambition related to students’ expectations and will, and ambition appears as academic achievement as it is tuned by important others such as parents, teachers, and peer students. The Wisconsin model believed that individuals or individual families could take coping strategies by emphasizing the social processes in the home as an early formative process. It means that unique parental roles, such as stimulating children through active communication, and high aspirations, make a significant difference in student’s educational achievement. The importance of family as a micro-network, especially intergenerational closeness, was emphasized. Furthermore, the Wisconsin model concluded that the above determinants are linked to the willingness to achieve academic achievement to acquire a job status. In particular, this study considered that high school choices such as MHS entrance, which were chosen by relational ambitions with parents, were related to students’ school life attitudes and performance of achievement norms.

Since then, studies have discussed strong influences of parents’ socioeconomic status rather than educational experiences emphasized by those status acquisition models (Goldthorpe, 2000; Jencks et al., 1979; Parkin, 1971). The privileged status class tends to try to ensure that their children’s generation can acquire similar hierarchical status, and these parental efforts result in a hereditary of social status. Therefore, students with higher social status gain excellent ability and motivation in school curriculum (Becker, 2009); it was confirmed that low-status students experienced considerable difficulties when transitioning from vocational training courses. From a comparable point of view, Beicht and Granato (2015) argued that there was a clear correlation between parents’ education and their socioeconomic status, and their social background plays an important role in the transition from school experience to vocational training. Noh (2012), Oh and Kim (2019) also assumed that household income affects the quality of jobs, and in particular, it was confirmed that the labor market performance of young Korean employees with high income was remarkable. These discussions highlight the determinants of social status acquisition that outweigh educational attainments.

Meanwhile, even in studies with different perspectives, “labor performance” has been regarded as a single indicator of social status. Blau and Duncan (1967) reported that inequality in economic status is at the root of the job structure. An individual’s performance in the labor market can be the total of previous experiences and resources (Becker, 2009; Parkin, 1971). Furthermore, the above mentioned studies agree that the process of personal performance and social status acquisition linked to the “family-school-labor market” is inevitable. School can be seen as a major mediating system that connects the family as a source of attributive status and the labor market as a vocational status acquisition market. Therefore, this study attempted to investigate the role of mediated secondary vocational education based on this premise discourse. In particular, as Korea’s representative secondary education policy, the positive role of education was assumed to focus on MHS.

The research questions of this study are as follows: First, is there a difference in the labor market performance of high school graduates by their parents’ socioeconomic status? Second, does secondary vocational education in MHS cause a difference in labor market performance of high school graduates?

4. Method

4.1. Data and instrument

This study integrated public dataset from the first year (2016) to the fourth year (2020) of the “Korean Education and Employment Panel (KEEP)” surveyed by the Korea Research Institute for Vocational Education & Training (KRIVET) as a governmental agency. Survey participants in KEEP’s 2016 were in their second year of high school, so they were early 20s adults in 2020. Furthermore, this study selected only samples corresponding to salary employees who graduated from high school. At the same time, samples such as those enrolled in university, unemployed and self-employed were excluded. Finally, 741 (31.6%) MHS graduates and 1,603 (68.4%) Specialized High Vocational School graduates (SVHS), a total of 2,344 data were used. What MHS and SVHS have in common is that, the proportion of specialized courses related to majors is higher than general courses in the curriculum, and practical classes are organized to learn vocational skills.

As shown in Table 1, the total variables of this study consist of 3 dimensions; high school characteristics influencing labor market performance, individual characteristics while attending high school, and labor market performance-related dimension. The variables adopted for labor market performance were designed in various ways. Representative variables that determine job status such as employment status, salary, and welfare were included, and satisfaction with job and life was added as an effect of labor market performance.

Table 1. Analysis variable in KEEP II

Dimension		Variable	Characteristics of variable	Data
Influencing factor	Characteristic of high school	School type	MSH = 1, SVHS = 2	1st
		School location	17 cities and provinces (Seoul = 1, Jeju = 17)	1st
	Individual characteristic	Father’s education level	None = 1, Elementary = 2, Middle school = 3, High school = 4, College = 5, University = 6, Master graduate = 7, Doctoral graduate = 8	1st
		Mother’s education level	None = 1, Elementary = 2, Middle school = 3, High school = 4, College = 5, University = 6, Master graduate = 7, Doctoral graduate = 8	1st
		Monthly income of household	Log value of the monthly income of household	1st
		Understanding of vocational courses	Understanding degree on the contents of vocational courses (Never = 1, Very much = 5)	1st, 2nd
		Participation of vocational courses	Participation hours of the vocational courses (Never = 1, Very much = 5)	1st, 2nd
Labor market performance		Employment status	Employment = 1, Unemployment = 2	4th
		Workplace size	Total number of employees (1 ~ 4 = 1, 5 ~ 9 = 2, 10 ~ 29 = 3, 30 ~ 49 = 4, 50 ~ 69 = 5, 70 ~ 99 = 6, 100–299 = 7, 300 ~ 499 = 8, 500 ~ 999 = 9, 1,000 or more = 10)	4th
		Working form	Regular = 1, Temporary = 2, Daily = 3	4th
		Job pattern	Permanent(full time) = 1, Permanent(part time) = 2, Non-permanent(full time) = 3, Non-permanent(part time) = 4	4th
		Monthly average salary	Log value of the monthly average salary	4th
		Labor contract	Less than 1 month = 1, More than 1 month~Less than 1 year = 2, More than 1 year~Less than 2 years = 3, More than 2 years~Less than 3 years = 4, More than 3 years = 5	4th
		After expiration of contract	Re-contract = 1, Indefinite contract = 2, Non-contract = 3, Fluid = 4	4th
		Type of working hours	Part time = 1, Full time = 2	4th
		Working days	Log value of the average working days per week	4th
		Working hours	Log value of the total working hours per week	4th
		welfare	Registration status of retirement benefits, bonuses, overtime pay, paid leave, corporate pension, national pension, national health insurance, employment insurance, industrial accident insurance (Yes = 1, No = 2)	4th
		Subjective labor market performance	Horizontal mismatch, Vertical mismatch, Job satisfaction, Wage satisfaction, Welfare satisfaction, Working hours satisfaction, Working environment satisfaction, Stability satisfaction (Never = 1, Very much = 5)	3rd, 4th
		Life satisfaction	Overall Satisfaction with High School Life, Overall Satisfaction with Workplace Life (Never = 1, Very much = 5)	1 ~ 4th

4.2. Research procedure

This study analyzed the educational roles of the secondary school policy and individual characteristics on labor market performance for salary employees of MHS graduation.

First, a propensity score matching (PSM) analysis was conducted to control characteristics that affect labor market performance, such as high school location, parents’ education level, and household income of MHS graduates and comparative high school graduates. This control characteristics consists of determinants proposed by Becker (2009), Goldthorpe (2000) and other studies emphasizing family status. Moreover, the comparison group was set as SVHS graduates hired as wage employees after high school graduation. PSM is a statistical analysis method that can satisfy the persuasive power of pure causal effects by controlling the selection convenience of the study target group and the comparison group, and is a method of extracting data with similar trends. (Felix, 2012; Rosenbaum & Rubin, 1983). And the key factors discussed as predictors in addition to the school effects were set as a covariate, and an independent sample t-test was conducted. Moreover, this study confirmed the multivariate balance after matching the school location, father and mother education level, and household income with a tendency score (0–1). Finally, we verified whether the equivalence between the graduate group of MHS and SVHS was secured for the covariate.

Next, the labor market performance by school types between MHS and SVHS was compared using the trend score matching data. This study conducted a multivariate analysis of variance (MANOVA) on outcome variables corresponding to labor market performance. However, these variables were considered not only labor market performance but also diverse objective and subjective performance, and at the same time, high correlation between each outcome variable. Multivariate analysis of variance can derive a difference in which outcome variables that cannot be revealed in a single variance analysis are combined. Through this, it is possible to reduce the type 1 error that appears to be different between groups due to repeated difference verification, although there is no difference between groups (Carey, 1998). In addition, multivariate analysis of variance can reveal the importance through combined scores between several outcome variables, so the labor market performance can be compared and verified in detail while considering the passage of time.

As factors influencing labor market performance, two-dimensional elements were used: school characteristic and school characteristic interacted with individual nature. As a single factor, school characteristics are related to the educational experience emphasized in Blau and Duncan’s (1967) status acquisition model. In addition, an individual factor as achievement academic performance assumed by the Wisconsin Model (Sewell et al., 1969) was set in the high school’s vocational courses designed for employment. As well as, variables of participation in vocational courses were used as individual characteristics. Specifically, the interaction of the variables “Understanding of vocational courses” and “Participation in vocational courses” was created to replace academic achievement.

5. Results

5.1. PSM on predictors of labor market performance

This study examined whether there is a difference between MHS graduates (experimental group) and SVHS graduates (comparative group), which have been discussed as major predictors of labor market performance. As a result, all four predictors had statistically significant differences, and the parent education level and monthly household income of MHS graduates were relatively higher than those of the comparative group.

Therefore we calculated the trend scores and adjusted that each characteristic of the two groups has the same distribution. After PSM analysis, the balance approached zero, as shown in Figure 1; there was no statistically significant difference between the four factors, as shown in Table 2. So the data of 2 groups secured homogeneity for the main predictors affecting labor market performance.

Figure 1. PSM Graph (Density balance)

Table 2. PSM on predictors of labor market performance

Predictors		Before PSM (n = 2,344)				After PSM (n = 1,166)
		MHS (n = 741)	SVHS (n = 1,603)	Mean difference	t-value	MHS (n = 694)	SVHS (n = 472)	Mean difference	t-value
School Location (%)	Seoul	5.5	13.7	0.753	3.694***	5.3	8.9	0.096	0.244
	Busan	8.4	7.3			8.6	8.5
	Daegu	6.3	4.9			6.2	4.9
	Incheon	4.9	7.9			4.5	6.8
	Gwangju	2.8	3.2			2.6	2.8
	Deajeon	7.1	2.5			6.6	3.4
	Ulsan	10.4	2.9			10.1	5.1
	Gyeonggi	5.9	18.5			6.2	11.7
	Kangwon	3.8	2.2			4	3.2
	Chungcheong	13.5	10.7			13.8	12.7
	Jeolla	15.2	11.9			15.6	15.7
	Gyeongsang	16.2	12.4			16.4	15.1
	Jeju	0	1.9			0	1.5
Father Edu-level(%)	High school below	57.6	69.3	0.251	5.393***	57.6	63.1	0.143	1.873
	Undergraduate	39.5	28.9			39.5	35.2
	Graduate	2.9	1.8			2.9	1.7
Mother Edu-level(%)	High school below	59.2	73.7	0.38	8.560***	58.4	64.6	0.073	0.083
	Undergraduate	38.5	24.9			39.2	34.1
	Graduate	2.3	1.4			2.4	1.3
Household income (Monthly, Won)		471.5	427.8	43.739	3.096**	479.3	469.5	9.738	0.614

*PSM formula (Rosenbaum & Rubin, 1983): e_i = Pr(Z_i = 1|X_i), the probability of conditional treatment assignment on observed baseline covariates

***p < .01, ***p < .001

5.2. Labor market performance gaps

Next, objective performances were compared using only controlled data through PSM analysis. Furthermore, it was found that MHS graduates had significantly higher objective labor performance than SVHS graduates, as shown in Table 3.

Table 3. Objective labor market performances

Objective Labor Market Performance	MHS		SVHS		t-value
	M	SD	M	SD
Current status of employment	1.47	0.5	1.65	0.47	−4.269***
Workplace size	7.35	2.76	4.76	3.1	7.685***
Job pattern	1.09	0.28	1.24	0.49	−3.906***
Work type	1.28	0.72	1.72	1.12	−4.713***
Monthly salary	224.73	57.53	184.63	55.25	5.050***
Working contract period	3.07	0.88	2.98	1.11	0.276
Situation after the contract	1.33	0.61	2.13	1.34	−3.975***
Working hours type	1.94	0.24	1.76	0.42	5.323***
Working days per week	5.13	0.57	4.91	0.89	2.106*
Working hours per week	42.13	10.05	38.2	14.39	3.053**
Severance pay	1.13	0.33	1.21	0.41	−2.066*
Bonus	1.2	0.4	1.42	0.49	−4.479***
Overtime pay	1.23	0.42	1.41	0.49	−3.506**
Paid vacation	1.23	0.42	1.49	0.5	−5.068***
Corporate pension	1.71	0.45	1.88	0.32	−3.103**
National pension	1.11	0.31	1.25	0.43	−3.373**
National health insurance	1.06	0.24	1.17	0.37	−3.471**
Unemployment insurance	1.1	0.3	1.17	0.37	−1.888
Industrial injury insurance	1.09	0.28	1.18	0.38	−2.587*

**p < .05, **p < .01, ***p < .001

They obtained better conditions in the following areas; the current employment status associated with the employment rate (t = −4.269, p < .001), as well as the workplace size, which is the standard for the preferred workplace (t = 7.685, p < .001), and the job pattern (t = −3.906, p < .001) and work type (t = −4.713, p < .001). Also, they get higher salaries (t = 5.050, p < .001), and showed significantly higher labor market performance in terms of welfare benefits. In terms of working days or hours, MHS graduates were higher with an average of 5.13 days and 42.13 hours per week. These results can be understood as the result of MHS graduates working as regular or full-time employees.

Moreover, as shown in Table 4, we compared the detailed dimensions of job-related satisfaction as subjective labor market performance.

Table 4. Subjective labor market performance

Subjective Performance	Descriptive statistics				MANOVA
	MHS		SVHS		School type	School type × Vocational courses achievement
	M	SD	M	SD	F-value (Pillai’s Trace)	F-value (Pillai’s Trace)
Horizontal mismatch(1st year)	3.59	0.89	3.23	1	6.202**	3.126***
Horizontal mismatch(2nd year)	3.68	0.88	3.26	0.93	9.936**	2.466***
Vertical mismatch(1st year)	2.75	0.48	2.97	0.57	7.062**	1.595*
Vertical mismatch(2nd year)	3.09	0.67	3.04	0.61	0.264	0.863
Job satisfaction(1st year)	3.82	0.66	3.49	0.8	8.718**	1.659*
Job satisfaction(2nd year)	3.45	0.78	3.42	0.75	0.046	1.372
Wage satisfaction(1st year)	3.73	0.77	3.34	0.95	8.811**	1.083
Wage satisfaction(2nd year)	3.43	0.83	3.23	0.88	2.609	1.109
Welfare satisfaction(1st year)	3.64	0.88	3.34	0.98	4.791*	1.399
Welfare satisfaction(2nd year)	3.41	0.95	3.29	0.91	0.844	1.029
Satisfaction with working hours(1st year)	3.84	0.85	3.7	0.92	1.153	2.022**
Satisfaction with working hours(2nd year)	3.7	0.91	3.6	0.82	0.685	1.299
Satisfaction with working environment(1st year)	3.73	0.65	3.74	0.79	0.001	1.411
Satisfaction with working environment(2nd year)	3.63	0.8	3.6	0.81	0.036	1.749*
Stability satisfaction(1st year)	3.75	0.84	3.6	0.86	1.419	1.746*
Stability satisfaction(2nd year)	3.66	0.9	3.56	0.81	0.774	1.263

*Significance of School type (Blau & Duncan model): Pillai’s Trace = 0.129, F(20,380) = 2.820, p = 0.000

*Significance of School type×Vocational courses achievement (Wisconsin model): Pillai’s Trace = 1.434, F(464, 5584) = 1.185, p = 0.005

**p < .05, **p < .01, ***p < .001

In the differences between groups, it was found that MHS graduates’ satisfaction was higher in the following areas; horizontal mismatch (F = 6.202, p < .01), job satisfaction (F = 8.718, p < .01), wage satisfaction (F = 8.811, p < .01), welfare satisfaction (F = 4.791, p < .05). However, the degree of vertical mismatch was significantly higher until the first year (F = 9.936, p < .01), and the satisfaction had no significant difference in the second year.

Based on the Wisconsin model, we examined whether there is a difference in labor market performance by the interaction between high school type and achievement level of the vocational course. This study was designed to confirm whether each student’s academic achievement affects future vocational performance in connection with the external environmental characteristics of the school. MHS graduates’ satisfaction is significantly higher during the working hours (F = 2.022, p < .01), working environment (F = 1.749, p < .05), and stability (F = 1.746, p < .05). However, it was found that there was no difference between wage and welfare satisfaction.

The detailed results of job satisfaction can be synthesized as follows. Wage employees who graduated from MHS continue to be satisfied with the work in the early stages of entering the labor market. And their subjective satisfaction with wages and welfare was high at the beginning of their employment.

Finally, life satisfaction was compared as an effect of educational achievement and labor market performance during high school or after employment (Table 5). MHS graduates showed significantly higher satisfaction in initial work-life (F = 10.154, 6.345), but there was no significant difference in school life satisfaction. Next, when vocational courses achievement interacts with the high school type, high school life satisfaction, which had no significant difference between groups, appeared the greatest difference in a relatively significant difference. (F = 3.392, 2.108). The results explain that the higher level of achievement in vocational courses, the satisfaction with high school life be different.

Table 5. Effects of labor market performance

Satisfaction	Descriptive statistics				MANOVA
	MHS		SVHS		School type	School type ×
						Vocational courses achievement
	M	SD	M	SD	F-value	F-value
					(Pillai’s Trace)	(Pillai’s Trace)
School-life(1^st year)	3.85	0.87	3.73	0.77	1	3.392***
School-life(2^nd year)	3.92	0.71	3.87	0.73	0.275	2.108**
Work-life(1^st year)	3.9	0.53	3.56	0.74	10.154**	1.756**
Work-life(2^nd year)	3.73	0.66	3.45	0.76	6.345*	1.798**

*Significance of School type (Blau & Duncan model): Wilk’s Lambda = 0.956, F(8, 372) = 2.125, p = 0.033

*Significance of School type×Vocational courses achievement (Wisconsin model): Pillai’s Trace = 0.915, F(232, 2800) = 1.558, p = 0.000

**p < .05, **p < .01, ***p < .001

6. Discussion and conclusions

This study attempted to understand the mechanism of labor market performance by confirming the role of secondary vocational education for young Korean employees who graduated from high school. Furthermore, we supported the Blau and Duncan (1967) model and Wisconsin model in the context that vocational education experiences could achieve labor market performance.

First, despite controlling parental status and school locations, it was significantly demonstrated the school roles of MHS as a crucial predictor of labor market performance, unlike the assumptions of K. Kim (2017), N. Kim (2019), and Oh and Kim (2019)’s studies. In many previous studies, MHS, which is in charge of secondary vocational education, showed positive labor market performance in terms of employment rate compared to SVHS (N. Kim, 2019; J. Kim et al., 2014; Yu & Lee, 2020). On the other hand, some discussions about MHS graduates’ labor market performance result from excellent students applying (K. Kim, 2017; N. Kim, 2019; Yang & Kim, 2014). This study attempted to control the main predictors of labor market performance, which is what the above-opposed discussions underline in common. In particular, it was found that MHS students’ secondary educational experience achieved a high objective performance level such as employment rate, wage, and welfare benefits. It can be understood that the MHS policy promoting diversification, specialization, and automation of secondary education worked positively in deriving students’ performance.

Second, the results of subjective labor performance were partially confirmed compared to the objective performance. Among them, significant differences continued in horizontal mismatch, indicating that MHS graduates’ school experiences and satisfaction with job matching were remarkable. Skill matching has been discussed as a key factor influencing job satisfaction and turnover (Peters & Kostas, 2020) and has become a global issue as a factor that hinders successful labor market performance along with over-education. In this regard, Green and Zhu (2010) argued that over-education (vertical mismatch) itself does not significantly affect job satisfaction but greatly reduces job satisfaction when combined with skill mismatch (as a horizontal mismatch). Even in countries such as Sweden and the United States, where skill mismatch is reported to be relatively low compared to Korea, the phenomenon of skill mismatch remains an important challenge (OECD, 2017). In detail, about 20% of college graduate employees have skill mismatch and are experiencing wage penalties. Through the preceding studies above, matching skills can be seen as a decisive influencing factor that leads to job satisfaction. This study used government-oriented survey data and confirmed that the Korean secondary vocational education policy satisfies the job quality for young wage employees by realizing continuous horizontal mismatch.

Thirdly, in the school roles of MHS, the labor market performance tended to increase when individual educational achievement interacted, and it was related to the Wisconsin model of status acquisition theory. Specifically, it was found that the higher the achievement of vocational courses among MHS students, the higher the life satisfaction as an influence on labor market performance. In addition, when secondary vocational courses subject achievement interacted, MHS students’ satisfaction significantly increased, which showed that the difference in high school life satisfaction significantly impacted individual student characteristics. The results demonstrate the Wisconsin model assumed in this study. It was confirmed that the MHS policy satisfies the assumptions of Sewell et al. (1969) status acquisition theory. The process of selecting MHS was carried out by their ambition and parents’ response as an important advisor, and this choice led to the student’s school life attitude and achievement. Overall, a student’s academic achievement is transferred to his/her human capital through the mechanism of “relational ambitions in education” between parents and children.

According to the results, it is worth noting that each high working conditions and their subjective satisfaction are characteristics to be discussed at different levels. It means that the labor market performance should be clearly identified as a significant indicator of social status. Unlike the significant difference in working conditions through secondary vocational education experiences, both MHS and SVHS graduates showed a decrease in subjective satisfaction after one year of early employment. Regarding this trend, it is pointed out that MHS’s school effect does not last (B. J. Kim, 2014; N. Kim, 2019). However, the offsetting of job satisfaction need to be understood as the overall nature of wage employees that change as subjective perception. In addition, after the early stages of working life, the structural characteristics of the unstable labor market, the growth of needs at the individual level, and heterogeneous labor market experiences between individuals are combined, offsetting the influence of vocational preparation education (Green & Zhu, 2010; B. H. Lee, 2002).

Therefore it need to reconsider whether it is reasonable to set life satisfaction as performance indicators as the policy outcomes for changes in students’ positive lives. Because the transition from school to workplace is diagnosed from a holistic perspective beyond the performance confirmed at each implementation stage (Oh & Kim, 2019; Peters & Kostas, 2020). In particular, in the case of major agreement revealed in this study, the performance of MHS graduates in the labor market is closely related to social issues such as employer’s preference to generate over-education, excessive enthusiasm for education, and popularization of higher education. Therefore, rather than the policy vision of overcoming social conditions and workplace culture and achieving successful labor market performance in secondary vocational education, it is necessary to focus on policy planning to maintain major consistency for secondary vocational students who expect successful vocational activities.

Although the above-described degree of horizontal mismatch is presented as a strong labor market achievement, academic discussions are insufficient at home and abroad compared to the degree of academic consensus. This may be because research is possible when data such as the job in charge of the workplace, the type of qualification to hold, and the type of qualification required for a specific job are organized. Therefore, we propose a follow-up study on the influencing factors and performance of skill mismatch, which combines analysis data used in this study with workplace case data with representativeness. Moreover, participation and understanding in the vocational course used in this study have limitations in differentiating students’ natures. It is necessary to pay attention to individual cases of students in order to closely discover personal experiences and achievements in MHS schools. Furthermore, in the curriculum and teaching method of secondary education, it need to more specifically distinguish personal perception of discipline between teachers and students and intellectualism.

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Conflict of interest

The authors have no competing interests to declare that are relevant to the content of this article.

Availability of data and materials

This study used public open data of KEEP(Korean Education & Employment Panel Survey) from Korea Research Institute for Vocational Education & Training(KRIVET) with a focus on Vocational Education in MHS and SVHS.

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No potential conflict of interest was reported by the author(s).

Additional information

Funding

Open access funding provided by KRIVET

Notes on contributors

Kyung Hee Park

Kyung Hee Park (First author) received her PhD in Sociology of education and is currently an assistant professor in department of education at Woosuk University in South Korea. The special areas of expertise are lifelong education and global citizenship education.

Jinyoung Yu received her PhD in history of vocational education at the Leibniz University of Hannover and is an Associate Research Fellow at the Korea Research Institute for Vocational Education & Training (KRIVET). She serves as the Researcher at the Center for Secondary vocational education in the KRIVET and has research interests in teacher training programs, vocational high school evaluation and certification systems for individual schools.